Gemini 4 Argon (effort medium · thinking on) on Sailboat instrument dashboard from an NMEA 0183 log
GGemini 4 Argonmedium · thinking on · Antigravity CLI 1.4.5 (agy -p) · cloud · 2026-10-22 · by @bobsiopener
- Estimated cost
- $0.45
- Wall time
- 8m
- Human step-ins
- 0
- Outcome
- Pass
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Summary
Exact prompt
# Sailboat instrument dashboard from an NMEA 0183 log `log.nmea` is a **synthetic** instrument log from a sailboat; `input.json` names it and gives alarm thresholds. Write `solve.py` (Python 3 standard library only) so that `python solve.py input.json answer.json` parses the log, computes true wind and VMG, finds alarm periods, writes `answer.json`, **and** writes a static display `dashboard.html` in the working directory. We re-run it on fresh logs, so do not hard-code anything. ## Log format Each line is `<t>,<sentence>` where `<t>` is an integer second and `<sentence>` is an NMEA 0183 sentence `$<body>*<hh>`. The checksum hh is two hex digits (either case) equal to the XOR of all characters of `<body>` (between `$` and `*`). ## Rules 1. Blank lines are ignored and not counted. A line is **malformed** if it has no comma before the sentence, `<t>` is not an integer, the sentence does not start with `$`, has no `*`, the checksum is not exactly 2 hex digits, or (after the checksum passes) the sentence type is not one of those below or a needed field is missing or not a number. A line whose checksum does not match is **bad_checksum**. Every other line is **valid** (this includes MWV lines that are skipped by rule 3). 2. The sentence type is the last 3 characters of the first field. Fields are split on commas (field 0 is the talker+type): - `HDT`: field 1 = true heading (degrees). - `VHW`: field 5 = boat speed through water (knots). - `DBT`: field 3 = depth (metres). - `VTG`: field 5 = speed over ground (knots). - `MWV`: field 1 = apparent wind angle (degrees clockwise from the bow, 0-360), field 2 = reference, field 3 = apparent wind speed (knots), field 5 = status. 3. Keep the latest heading and boat speed. For an MWV with reference `R` and status `A`, if a heading and a boat speed have already been seen, make a **true wind sample** at its time: x = AWS*cos(AWA) - BSP, y = AWS*sin(AWA); TWS = hypot(x, y); TWA = atan2(y, x) in degrees mod 360; TWD = (heading + TWA) mod 360; VMG = BSP*cos(TWA). MWV lines with another reference or status are valid but make no sample. 4. Alarms: depth alarm on DBT readings with depth < `depth_min`; wind alarm on true wind samples with TWS > `tws_max`; speed alarm on VTG readings with SOG > `sog_max`. For each type, an alarm is a maximal run of consecutive readings of that type (in file order) that break the limit; `start`/`end` are the times of its first and last breaking reading. Sort all alarms by start, then type name. 5. `last` holds the last sample's tws, twa, twd, vmg (2 decimals) and the last boat speed and depth values as read. ## answer.json `{"counts": {"valid", "bad_checksum", "malformed"}, "true_wind_samples": n, "last": {"tws", "twa", "twd", "vmg", "bsp", "depth"}, "tws_mean": .., "tws_max": .., "alarms": [{"type": "depth"|"wind"|"speed", "start", "end"}, ...]}` (mean and max of TWS over all samples, 2 decimals). ## dashboard.html A self-contained static page (no scripts or network needed) with these element ids: `tws`, `twa`, `twd`, `vmg`, `bsp`, `depth` (each element's text is only the value from `last` with 1 decimal), an `<svg id="wind-rose">` containing a `<line id="twd-needle">` pointing toward TWD, and `<ul id="alarm-list">` with exactly one `<li>` per alarm. Styling is up to you. It must be static and self-contained so it can be screenshotted headless: no `<script>`, no `<img>`/`<link>`/`<iframe>`/`<object>`/`<embed>`, no `on*` handlers, no `href`/`src` except `#...` or `data:`, no CSS `url(http...)` or `@import`, no fetches. ## Scoring Hidden checks (partial credit = fraction passed; all must pass): `sentence_counts` (exact), `true_wind_and_vmg` (within 0.011, sample count exact), `alarm_intervals` (exact), `dashboard_elements` (file exists, static rules above, ids present, `wind-rose` is `<svg>`, `twd-needle` is `<line>`, `alarm-list` is `<ul>`), `dashboard_values` (each value within 0.051 of the answer, li count) on the given log; `fresh_log_1` (all answer keys plus dashboard values) and `fresh_log_2` (all answer keys) on fresh logs. Each run has a 60-second limit.
Checksum XOR with lowercase hex, malformed vs bad-checksum vs skipped MWV, true wind from apparent wind with the latest heading and speed, alarm runs per reading type, and a static HTML display whose values are cross-checked. Original benchmark task written for usecaserank.com. Headless, offline run on a reproducible fixture. Cost shown is a list-price API-equivalent estimate (run on a Google account via Antigravity CLI, not billed per token).
Benchmark code for comparing AI models, not navigation or safety software.
Success criteria: 1. sentence_counts 2. true_wind_and_vmg 3. alarm_intervals 4. dashboard_elements 5. dashboard_values 6. fresh_log_1 7. fresh_log_2
Setup notes: Use Case Scout batch10 case k01-nmea-instrument-dashboard (offline fixture). Prepared with batch10/prepare.sh on the shared box; only TASK.md + starting files went to the agent machine, hidden keys stayed on the box. Prompt = TASK.md verbatim. Flags: -p --model gemini-4-argon-medium --sandbox --dangerously-skip-permissions --disable-slash-commands --output-format stream-json, cwd=workdir. Scored on the box with `python score.py WORKDIR KEYDIR`. Single run, no retries, no human input. Visual output (dashboard.html) rendered offline to PNG with google-chrome headless, network blocked, 1280x800 at ~3 s after load. Requested model gemini-4-argon-medium (effort medium); priced at the base model row gemini-4-argon (pricing.json, https://ai.google.dev/gemini-api/docs/pricing). Score: 7/7. Cost is an ESTIMATE: measured tokens x pricing.json list price (Google account, nothing billed per token); output_tokens include thinking tokens. Tool calls 18 (0 failed). Single run.
Estimated cost List-price estimate; not actually billed.
Output
Metrics
- Estimated cost
- $0.45
- Wall time
- 8m
- Human step-ins
- 0
- Turns
- 17
| Model | Input tok | Output tok | Cost |
|---|---|---|---|
| GGemini 4 Argongoogle/gemini-4-argoneffort medium · thinking on | 674,057 | 24,707 | $0.45 |
Reproduce this run
- Use the use case prompt on the use case page.
- Same setup: Gemini 4 Argon (google/gemini-4-argon, effort medium · thinking on) via
Antigravity CLI 1.4.5 (agy -p), cloud. - It counts as a success only if it meets every success criterion: 1. sentence_counts 2. true_wind_and_vmg 3. alarm_intervals 4. dashboard_elements 5. dashboard_values 6. fresh_log_1 7. fresh_log_2
- Log model, tokens, wall time, human step-ins and the evidence log, then submit it as a reproduction. A different model? Submit a head-to-head rerun.
How runs are scored: Methodology.
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Automated checks
Trust 80% comes from these checks (how Trust % works).
- Run date is not in the future : passed
- Model is in the dated pricing table : passed
- Cost recomputed from tokens matches : passed
- Cached tokens are consistent : passed
- Output throughput is plausible : passed
- Autonomy matches step-ins : passed
- Step-ins do not exceed turns : passed
- Retries agree with first-try result : passed
- Evidence log SHA-256 matches : passed
- Evidence log is substantial : passed
Evidence log
{"event": "init", "conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "init": {"model": "gemini-4-argon-medium", "cwd": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work", "tools": ["ask_custom_permission", "ask_permission", "ask_question", "browser_click_element", "browser_drag_pixel_to_pixel", "browser_get_dom", "browser_get_network_request", "browser_input", "browser_list_network_requests", "browser_mouse_down", "browser_mouse_up", "browser_move_mouse", "browser_press_key", "browser_refresh_page", "browser_resize_window", "browser_scroll", "browser_scroll_dom", "browser_select_option", "browser_subagent", "call_mcp_tool", "capture_browser_console_logs", "capture_browser_screenshot", "click_browser_pixel", "command_status", "define_subagent", "delete_knowledge", "execute_browser_javascript", "find_by_name", "finish", "generate_image", "grep_search", "invoke_subagent", "list_browser_pages", "list_dir", "list_permissions", "list_plugin_accounts", "list_resources", "manage_inbox", "manage_subagents", "manage_task", "multi_replace_file_content", "notebook_edit", "notebook_execution", "open_browser_url", "read_browser_page", "read_resource", "read_url_content", "replace_file_content", "run_command", "run_workflow", "schedule", "search_marketplace", "search_web", "sed_file", "send_command_input", "send_message", "view_file", "wait", "wait_5_seconds", "write_to_file"], "permission_mode": "always-proceed"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 0, "state": "DONE", "step_type": "user_input"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 1, "state": "DONE", "step_type": "agent_response", "duration_seconds": 14.3903592, "usage": {"input_tokens": 8978, "output_tokens": 184, "thinking_tokens": 67, "cache_read_tokens": 0, "total_tokens": 9162}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 2, "state": "ACTIVE", "step_type": "tool", "tool_name": "read_file", "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/input.json"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 2, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.492984087, "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/input.json"}, "output": "8 lines, 95 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 3, "state": "ACTIVE", "step_type": "tool", "tool_name": "read_file", "tool_info": {"name": "read_file", "parameters": {"EndLine": 100, "Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/log.nmea", "StartLine": 1}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 3, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.20111157, "tool_info": {"name": "read_file", "parameters": {"EndLine": 100, "Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/log.nmea", "StartLine": 1}, "output": "502 lines, 14141 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 4, "state": "DONE", "step_type": "agent_response", "duration_seconds": 38.309228182, "usage": {"input_tokens": 3120, "output_tokens": 101, "thinking_tokens": 32, "cache_read_tokens": 8979, "total_tokens": 3221}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 5, "state": "ACTIVE", "step_type": "tool", "tool_name": "read_file", "tool_info": {"name": "read_file", "parameters": {"EndLine": 502, "Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/log.nmea", "StartLine": 101}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 5, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.156434381, "tool_info": {"name": "read_file", "parameters": {"EndLine": 502, "Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/log.nmea", "StartLine": 101}, "output": "502 lines, 14141 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 6, "state": "DONE", "step_type": "agent_response", "duration_seconds": 19.027285243, "usage": {"input_tokens": 11759, "output_tokens": 1101, "thinking_tokens": 572, "cache_read_tokens": 12100, "total_tokens": 12860}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 7, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nwith open(\"log.nmea\") as f:\n for idx, line in enumerate(f, 1):\n s = line.strip()\n if not s:\n print(f\"Line {idx}: BLANK\")\n continue\n if \",\" not in s:\n print(f\"Line {idx}: NO COMMA: {s}\")\n continue\n t_str, sent = s.split(\",\", 1)\n try:\n int(t_str)\n except ValueError:\n print(f\"Line {idx}: BAD T: {s}\")\n continue\n if not sent.startswith(\"$\") or \"*\" not in sent:\n \u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 7, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 1.9109531770000001, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nwith open(\"log.nmea\") as f:\n for idx, line in enumerate(f, 1):\n s = line.strip()\n if not s:\n print(f\"Line {idx}: BLANK\")\n continue\n if \",\" not in s:\n print(f\"Line {idx}: NO COMMA: {s}\")\n continue\n t_str, sent = s.split(\",\", 1)\n try:\n int(t_str)\n except ValueError:\n print(f\"Line {idx}: BAD T: {s}\")\n continue\n if not sent.startswith(\"$\") or \"*\" not in sent:\n \u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nLine 25: BAD CS (3b != 1a): 12,$IIMWV,77.7,R,17.7,N,A*1a\r\nLine 54: HAS x in field 1 (VTG): 30,$GPVTG,x328.8,T,,M,5.11,N,,K*02\r\nLine 95: HAS x in field 1 (MWV): 54,$IIMWV,x62.3,R,17.5,N,A*41\r\nLine 117: HAS x in field 1 (VHW): 69,$IIVHW,x,T,,M,5.45,N,,K*37\r\nLine 147: BAD CS (43 != 62): 87,$IIVHW,,T,,M,5.58,N,,K*62\r\nLine 182: BAD CS (48 != 69): 108,$IIVHW,,T,,M,5.35,N,,K*69\r\nLine 209: BAD CS (75 != 54): 123,$GPVTG,341.8,T,,M,6.30,N,,K*54\r\nLine 247: BAD CS (4c != 6D): 147,$IIVHW,,T,,M,5.31,N,,K*6D\r\nLine 262: BAD CS (4e != 6F): 156,$IIVHW,,T,,M,5.22,N,,K*6F\r\nLine 266: BLANK\r\nLine 276: MWV non-R/A: 162,$IIMWV,52.6,R,20.5,N,V*2C\r\nLine 277: UNKNOWN TYPE: 162,$IIXDR,C,19.5,C,AIR*07\r\nLine 284: HAS x in field 1 (VHW): 168,$IIVHW,x,T,,M,4.59,N,,K*3b\r\nLine 300: NO $ OR *: 177,$IIDBT,,f,7.4,M,,F\r\nLine 325: BAD CS (1e != 3F): 192,$IIDBT,,f,6.9,M,,F*3F\r\nLine 333: BAD CS (25 != 04): 198,$IIHDT,334.3,T*04\r\nLine 339: BAD CS (4f != 6e): 201,$IIVHW,,T,,M,5.76,N,,K*6e\r\nLine 344: BAD CS (42 != 63): 204,$IIVHW,,T,,M,5.95,N,,K*63\r\nLine 367: MWV non-R/A: 216,$IIMWV,51.5,R,19.0,N,V*23\r\nLine 376: BAD CS (71 != 50): 222,$GPVTG,335.2,T,,M,5.49,N,,K*50\r\nLine 404: HAS x in field 1 (VHW): 240,$IIVHW,x,T,,M,5.00,N,,K*36\r\nLine 456: HAS x in field 1 (VTG): 270,$GPVTG,x327.8,T,,M,5.17,N,,K*0B\r\nLine 477: MWV non-R/A: 282,$IIMWV,59.4,R,20.3,N,V*23\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 8, "state": "DONE", "step_type": "agent_response", "duration_seconds": 57.240158428, "usage": {"input_tokens": 2103, "output_tokens": 2695, "thinking_tokens": 2534, "cache_read_tokens": 23860, "total_tokens": 4798}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 9, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nwith open(\"log.nmea\") as f:\n lines = [l.strip() for l in f]\nfor idx in [54, 95, 117, 284, 404, 456]:\n print(f\"=== Around line {idx} ===\")\n for i in range(max(0, idx-3), min(len(lines), idx+4)):\n print(f\"{i+1}: {lines[i]}\")\n'"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 9, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 1.441565295, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nwith open(\"log.nmea\") as f:\n lines = [l.strip() for l in f]\nfor idx in [54, 95, 117, 284, 404, 456]:\n print(f\"=== Around line {idx} ===\")\n for i in range(max(0, idx-3), min(len(lines), idx+4)):\n print(f\"{i+1}: {lines[i]}\")\n'"}, "output": "Command exited with code 0.\n\nCommand output:\n=== Around line 54 ===\r\n52: 30,$IIVHW,,T,,M,4.98,N,,K*4E\r\n53: 30,$IIDBT,,f,8.9,M,,F*10\r\n54: 30,$GPVTG,x328.8,T,,M,5.11,N,,K*02\r\n55: 30,$IIMWV,71.4,R,19.6,N,A*31\r\n56: 33,$IIHDT,329.0,T*2a\r\n57: 33,$IIVHW,,T,,M,5.15,N,,K*4A\r\n58: 33,$IIDBT,,f,8.4,M,,F*1D\r\n=== Around line 95 ===\r\n93: 54,$IIDBT,,f,7.6,M,,F*10\r\n94: 54,$GPVTG,336.3,T,,M,5.33,N,,K*7E\r\n95: 54,$IIMWV,x62.3,R,17.5,N,A*41\r\n96: 57,$IIHDT,338.1,T*2B\r\n97: 57,$IIVHW,,T,,M,5.34,N,,K*49\r\n98: 57,$IIDBT,,f,8.2,M,,F*1B\r\n99: 57,$GPVTG,338.1,T,,M,5.03,N,,K*71\r\n=== Around line 117 ===\r\n115: 66,$IIMWV,56.5,R,16.7,N,A*3B\r\n116: 69,$IIHDT,340.2,T*27\r\n117: 69,$IIVHW,x,T,,M,5.45,N,,K*37\r\n118: 69,$IIDBT,,f,7.7,M,,F*11\r\n119: 69,$GPVTG,340.2,T,,M,6.27,N,,K*78\r\n120: 69,$IIMWV,54.2,R,17.3,N,A*3B\r\n121: 72,$IIHDT,342.5,T*22\r\n=== Around line 284 ===\r\n282: 165,$IIMWV,53.0,R,21.0,N,A*38\r\n283: 168,$IIHDT,336.7,T*23\r\n284: 168,$IIVHW,x,T,,M,4.59,N,,K*3b\r\n285: 168,$IIDBT,,f,7.4,M,,F*12\r\n286: 168,$GPVTG,336.7,T,,M,5.13,N,,K*78\r\n287: 168,$IIMWV,48.1,R,19.5,N,A*3D\r\n288: 171,$IIHDT,332.2,T*22\r\n=== Around line 404 ===\r\n402: 237,$IIMWV,53.1,R,19.0,N,A*32\r\n403: 240,$IIHDT,334.3,T*25\r\n404: 240,$IIVHW,x,T,,M,5.00,N,,K*36\r\n405: 240,$IIDBT,,f,7.0,M,,F*16\r\n406: 240,$GPVTG,334.3,T,,M,5.25,N,,K*7B\r\n407: 240,$IIMWV,55.7,R,19.8,N,A*3a\r\n408: 243,$IIHDT,330.9,T*2B\r\n=== Around line 456 ===\r\n454: 270,$IIVHW,,T,,M,4.86,N,,K*41\r\n455: 270,$IIDBT,,f,7.8,M,,F*1e\r\n456: 270,$GPVTG,x327.8,T,,M,5.17,N,,K*0B\r\n457: 270,$IIMWV,57.7,R,19.1,N,A*31\r\n458: 273,$IIHDT,328.8,T*23\r\n459: 273,$IIVHW,,T,,M,4.67,N,,K*4E\r\n460: 273,$IIDBT,,f,7.9,M,,F*1f\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 10, "state": "DONE", "step_type": "agent_response", "duration_seconds": 33.149519697, "usage": {"input_tokens": 4018, "output_tokens": 2732, "thinking_tokens": 1878, "cache_read_tokens": 25964, "total_tokens": 6750}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 11, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, math\n\nwith open(\"input.json\") as f:\n cfg = json.load(f)\n\nvalid = bad_checksum = malformed = 0\nheading = None\nbsp = None\ndepth = None\ntw_samples = []\ndbt_readings = []\nvtg_readings = []\n\nwith open(cfg[\"log\"]) as f:\n for line in f:\n s = line.strip()\n if not s:\n continue\n if \",\" not in s:\n malformed += 1\n continue\n t_str, sent = s.split(\",\", 1)\n try:\n t = int(t_str)\n except ValueError:\n \u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 11, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 1.678196953, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, math\n\nwith open(\"input.json\") as f:\n cfg = json.load(f)\n\nvalid = bad_checksum = malformed = 0\nheading = None\nbsp = None\ndepth = None\ntw_samples = []\ndbt_readings = []\nvtg_readings = []\n\nwith open(cfg[\"log\"]) as f:\n for line in f:\n s = line.strip()\n if not s:\n continue\n if \",\" not in s:\n malformed += 1\n continue\n t_str, sent = s.split(\",\", 1)\n try:\n t = int(t_str)\n except ValueError:\n \u2026"}, "output": "Command exited with code 0.\n\nCommand output:\ncounts: {'valid': 487, 'bad_checksum': 11, 'malformed': 3}\r\ntw_samples: 95\r\nlast sample: (297, 17.35106677784368, 69.52334235467946, 47.72334235467946, 1.7701183004277277)\r\nlast bsp, depth: 5.06 5.6\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 12, "state": "DONE", "step_type": "agent_response", "duration_seconds": 48.512366502, "usage": {"input_tokens": 2960, "output_tokens": 2310, "thinking_tokens": 1636, "cache_read_tokens": 29983, "total_tokens": 5270}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 13, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, math\n\nwith open(\"input.json\") as f:\n cfg = json.load(f)\n\ndepth_min = cfg[\"alarms\"][\"depth_min\"]\ntws_max = cfg[\"alarms\"][\"tws_max\"]\nsog_max = cfg[\"alarms\"][\"sog_max\"]\n\nheading = bsp = None\nwith open(\"log.nmea\") as f:\n for idx, line in enumerate(f, 1):\n s = line.strip()\n if not s or \",\" not in s: continue\n t_str, sent = s.split(\",\", 1)\n t = int(t_str)\n if \"*\" not in sent:\n print(f\"MALFORMED at t={t}: {s}\")\n continue\n \u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 13, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 2.465399698, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, math\n\nwith open(\"input.json\") as f:\n cfg = json.load(f)\n\ndepth_min = cfg[\"alarms\"][\"depth_min\"]\ntws_max = cfg[\"alarms\"][\"tws_max\"]\nsog_max = cfg[\"alarms\"][\"sog_max\"]\n\nheading = bsp = None\nwith open(\"log.nmea\") as f:\n for idx, line in enumerate(f, 1):\n s = line.strip()\n if not s or \",\" not in s: continue\n t_str, sent = s.split(\",\", 1)\n t = int(t_str)\n if \"*\" not in sent:\n print(f\"MALFORMED at t={t}: {s}\")\n continue\n \u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nVTG t=0: sog=5.15 (alarm=False)\r\nVTG t=3: sog=5.29 (alarm=True)\r\nVTG t=6: sog=5.12 (alarm=False)\r\nVTG t=9: sog=5.25 (alarm=True)\r\nBAD_CS at t=12: 12,$IIMWV,77.7,R,17.7,N,A*1a\r\nVTG t=15: sog=5.01 (alarm=False)\r\nVTG t=21: sog=5.78 (alarm=True)\r\nVTG t=24: sog=5.04 (alarm=False)\r\nVTG t=27: sog=5.89 (alarm=True)\r\nMWV sample t=27: tws=18.665 (alarm=False)\r\nVTG t=30: sog=5.11 (alarm=False)\r\nMWV sample t=30: tws=18.620 (alarm=False)\r\nVTG t=33: sog=5.17 (alarm=False)\r\nVTG t=36: sog=5.74 (alarm=True)\r\nVTG t=39: sog=5.2 (alarm=False)\r\nVTG t=42: sog=5.52 (alarm=True)\r\nVTG t=45: sog=5.29 (alarm=True)\r\nVTG t=48: sog=5.47 (alarm=True)\r\nMWV sample t=48: tws=18.384 (alarm=False)\r\nVTG t=54: sog=5.33 (alarm=True)\r\nMALFORMED fields at t=54: 54,$IIMWV,x62.3,R,17.5,N,A*41\r\nVTG t=57: sog=5.03 (alarm=False)\r\nVTG t=60: sog=5.39 (alarm=True)\r\nVTG t=63: sog=5.78 (alarm=True)\r\nVTG t=66: sog=5.65 (alarm=True)\r\nVTG t=69: sog=6.27 (alarm=True)\r\nVTG t=72: sog=5.4 (alarm=True)\r\nVTG t=75: sog=5.96 (alarm=True)\r\nVTG t=78: sog=5.71 (alarm=True)\r\nVTG t=81: sog=5.86 (alarm=True)\r\nVTG t=84: sog=5.54 (alarm=True)\r\nMWV sample t=84: tws=19.281 (alarm=True)\r\nBAD_CS at t=87: 87,$IIVHW,,T,,M,5.58,N,,K*62\r\nVTG t=87: sog=5.94 (alarm=True)\r\nMWV sample t=87: tws=18.620 (alarm=False)\r\nVTG t=90: sog=5.71 (alarm=True)\r\nMWV sample t=90: tws=18.714 (alarm=False)\r\nVTG t=93: sog=5.94 (alarm=True)\r\nMWV sample t=93: tws=19.789 (alarm=True)\r\nVTG t=96: sog=5.71 (alarm=True)\r\nMWV sample t=96: tws=19.152 (alarm=False)\r\nVTG t=99: sog=5.44 (alarm=True)\r\nMWV sample t=99: tws=19.441 (alarm=True)\r\nVTG t=102: sog=5.27 (alarm=True)\r\nMWV sample t=102: tws=18.283 (alarm=False)\r\nVTG t=105: sog=5.7 (alarm=True)\r\nBAD_CS at t=108: 108,$IIVHW,,T,,M,5.35,N,,K*69\r\nVTG t=108: sog=5.6 (alarm=True)\r\nVTG t=111: sog=5.96 (alarm=True)\r\nVTG t=114: sog=5.14 (alarm=False)\r\nVTG t=117: sog=5.9 (alarm=True)\r\nVTG t=120: sog=6.04 (alarm=True)\r\nBAD_CS at t=123: 123,$GPVTG,341.8,T,,M,6.30,N,,K*54\r\nVTG t=126: sog=5.75 (alarm=True)\r\nVTG t=129: sog=6.13 (alarm=True)\r\nVTG t=132: sog=5.41 (alarm=True)\r\nVTG t=135: sog=5.08 (alarm=False)\r\nVTG t=141: sog=5.2 (alarm=False)\r\nMWV sample t=141: tws=18.438 (alarm=False)\r\nVTG t=144: sog=5.74 (alarm=True)\r\nMWV sample t=144: tws=18.284 (alarm=False)\r\nBAD_CS at t=147: 147,$IIVHW,,T,,M,5.31,N,,K*6D\r\nVTG t=147: sog=5.98 (alarm=True)\r\nMWV sample t=147: tws=18.707 (alarm=False)\r\nVTG t=150: sog=5.71 (alarm=True)\r\nVTG t=153: sog=5.39 (alarm=True)\r\nMWV sample t=153: tws=18.299 (alarm=False)\r\nBAD_CS at t=156: 156,$IIVHW,,T,,M,5.22,N,,K*6F\r\nVTG t=156: sog=5.9 (alarm=True)\r\nMWV sample t=156: tws=18.850 (alarm=False)\r\nMWV sample t=159: tws=18.990 (alarm=False)\r\nMWV skipped t=162: ref=R status=V\r\nMWV sample t=165: tws=18.504 (alarm=False)\r\nVTG t=168: sog=5.13 (alarm=False)\r\nVTG t=171: sog=5.48 (alarm=True)\r\nVTG t=174: sog=5.24 (alarm=True)\r\nMALFORMED at t=177: 177,$IIDBT,,f,7.4,M,,F\r\nVTG t=177: sog=5.44 (alarm=True)\r\nVTG t=180: sog=5.26 (alarm=True)\r\nVTG t=183: sog=5.25 (alarm=True)\r\nVTG t=186: sog=5.28 (alarm=True)\r\nBAD_CS at t=192: 192,$IIDBT,,f,6.9,M,,F*3F\r\nVTG t=195: sog=5.58 (alarm=True)\r\nBAD_CS at t=198: 198,$IIHDT,334.3,T*04\r\nVTG t=198: sog=6.01 (alarm=True)\r\nBAD_CS at t=201: 201,$IIVHW,,T,,M,5.76,N,,K*6e\r\nVTG t=201: sog=6.13 (alarm=True)\r\nMWV sample t=201: tws=18.215 (alarm=False)\r\nBAD_CS at t=204: 204,$IIVHW,,T,,M,5.95,N,,K*63\r\nVTG t=204: sog=6.26 (alarm=True)\r\nVTG t=207: sog=6.25 (alarm=True)\r\nDBT t=210: d=5.8 (alarm=True)\r\nVTG t=210: sog=6.41 (alarm=True)\r\nDBT t=213: d=5.7 (alarm=True)\r\nVTG t=213: sog=5.92 (alarm=True)\r\nDBT t=216: d=5.6 (alarm=True)\r\nVTG t=216: sog=5.88 (alarm=True)\r\nMWV skipped t=216: ref=R status=V\r\nVTG t=219: sog=5.38 (alarm=True)\r\nMWV sample t=219: tws=18.240 (alarm=False)\r\nBAD_CS at t=222: 222,$GPVTG,335.2,T,,M,5.49,N,,K*50\r\nVTG t=225: sog=6.07 (alarm=True)\r\nVTG t=228: sog=5.47 (alarm=True)\r\nVTG t=231: sog=5.14 (alarm=False)\r\nVTG t=234: sog=5.64 (alarm=True)\r\nVTG t=237: sog=5.71 (alarm=True)\r\nVTG t=240: sog=5.25 (alarm=True)\r\nVTG t=243: sog=5.1 (alarm=False)\r\nVTG t=246: sog=5.62 (alarm=True)\r\nMWV sample t=246: tws=18.842 (alarm=False)\r\nVTG t=249: sog=6.22 (alarm=True)\r\nVTG t=252: sog=5.77 (alarm=True)\r\nMWV sample t=252: tws=18.456 (alarm=False)\r\nVTG t=255: sog=6.28 (alarm=True)\r\nVTG t=258: sog=5.33 (alarm=True)\r\nVTG t=261: sog=5.25 (alarm=True)\r\nVTG t=264: sog=5.57 (alarm=True)\r\nMWV sample t=264: tws=19.137 (alarm=False)\r\nVTG t=267: sog=5.53 (alarm=True)\r\nMWV sample t=267: tws=19.042 (alarm=False)\r\nVTG t=270: sog=5.17 (alarm=False)\r\nVTG t=273: sog=5.45 (alarm=True)\r\nMWV skipped t=282: ref=R status=V\r\nVTG t=285: sog=5.37 (alarm=True)\r\nMWV sample t=285: tws=18.807 (alarm=False)\r\nVTG t=288: sog=5.01 (alarm=False)\r\nMWV sample t=288: tws=18.464 (alarm=False)\r\nDBT t=291: d=6.2 (alarm=False)\r\nVTG t=291: sog=5.59 (alarm=True)\r\nDBT t=294: d=5.7 (alarm=True)\r\nVTG t=294: sog=5.17 (alarm=False)\r\nDBT t=297: d=5.6 (alarm=True)\r\nVTG t=297: sog=5.22 (alarm=True)\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 14, "state": "DONE", "step_type": "agent_response", "duration_seconds": 29.854478167, "usage": {"input_tokens": 5282, "output_tokens": 1890, "thinking_tokens": 1273, "cache_read_tokens": 32944, "total_tokens": 7172}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 15, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, math\n\nwith open(\"input.json\") as f:\n cfg = json.load(f)\n\nheading = bsp = None\ntws_list = []\nwith open(\"log.nmea\") as f:\n for line in f:\n s = line.strip()\n if not s or \",\" not in s: continue\n t_str, sent = s.split(\",\", 1)\n t = int(t_str)\n if not sent.startswith(\"$\") or \"*\" not in sent: continue\n body, cs = sent[1:].split(\"*\", 1)\n if len(cs) != 2: continue\n xor = 0\n for c in body: xor ^= ord(c)\n if xor != int\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 15, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 1.73863985, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, math\n\nwith open(\"input.json\") as f:\n cfg = json.load(f)\n\nheading = bsp = None\ntws_list = []\nwith open(\"log.nmea\") as f:\n for line in f:\n s = line.strip()\n if not s or \",\" not in s: continue\n t_str, sent = s.split(\",\", 1)\n t = int(t_str)\n if not sent.startswith(\"$\") or \"*\" not in sent: continue\n body, cs = sent[1:].split(\"*\", 1)\n if len(cs) != 2: continue\n xor = 0\n for c in body: xor ^= ord(c)\n if xor != int\u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nUnrounded mean: 17.39 17.388470946080357\r\nRounded mean: 17.39\r\nUnrounded max: 19.79 19.788968616153518\r\nt=84: tws=19.280682, round(tws,2)=19.28\r\nt=96: tws=19.152012, round(tws,2)=19.15\r\nt=99: tws=19.440871, round(tws,2)=19.44\r\nt=264: tws=19.136964, round(tws,2)=19.14\r\nt=267: tws=19.041591, round(tws,2)=19.04\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 16, "state": "DONE", "step_type": "agent_response", "duration_seconds": 77.564165189, "usage": {"input_tokens": 2206, "output_tokens": 7183, "thinking_tokens": 2933, "cache_read_tokens": 38227, "total_tokens": 9389}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 17, "state": "ACTIVE", "step_type": "tool", "tool_name": "write_file", "tool_info": {"name": "write_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/solve.py"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 17, "state": "DONE", "step_type": "tool", "tool_name": "write_file", "duration_seconds": 1.99526782, "tool_info": {"name": "write_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/solve.py"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 18, "state": "DONE", "step_type": "agent_response", "duration_seconds": 17.199975118, "usage": {"input_tokens": 7268, "output_tokens": 95, "thinking_tokens": 32, "cache_read_tokens": 40434, "total_tokens": 7363}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 19, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 solve.py input.json answer.json && cat answer.json"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 19, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 2.092570259, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 solve.py input.json answer.json && cat answer.json"}, "output": "Command exited with code 1.\n\nCommand output:\nTraceback (most recent call last):\r\n File \"/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/solve.py\", line 388, in <module>\r\n parse_and_solve(sys.argv[1], sys.argv[2])\r\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/solve.py\", line 161, in parse_and_solve\r\n alarms.extend(find_alarms([(t, s[1]) for t, *s in [(x[0], x[1]) for x in tw_samples]], \"wind\", lambda w: w > tws_max_limit))\r\n ~^^^\r\nIndexError: list index out of range\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 20, "state": "DONE", "step_type": "agent_response", "duration_seconds": 8.749860881, "usage": {"input_tokens": 2431, "output_tokens": 197, "thinking_tokens": 42, "cache_read_tokens": 45653, "total_tokens": 2628}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 21, "state": "ACTIVE", "step_type": "tool", "tool_name": "edit_file", "tool_info": {"name": "edit_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/solve.py"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 21, "state": "DONE", "step_type": "tool", "tool_name": "edit_file", "duration_seconds": 2.124724629, "tool_info": {"name": "edit_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/solve.py"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 22, "state": "DONE", "step_type": "agent_response", "duration_seconds": 7.00424131, "usage": {"input_tokens": 2374, "output_tokens": 94, "thinking_tokens": 31, "cache_read_tokens": 46035, "total_tokens": 2468}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 23, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 solve.py input.json answer.json && cat answer.json"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 23, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 2.278243877, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 solve.py input.json answer.json && cat answer.json"}, "output": "Command exited with code 1.\n\nThere were sandbox errors that may or may not be related to the failure. If you think the failure is because of running in the sandbox, you can run the command again with `BypassSandbox` set to true to request explicit user permission.\n\nCommand output:\nTraceback (most recent call last):\r\n File \"/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/solve.py\", line 388, in <module>\r\n parse_and_solve(sys.argv[1], sys.argv[2])\r\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/solve.py\", line 198, in parse_and_solve\r\n with open(answer_path, \"w\", encoding=\"utf-8\") as f:\r\n ~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\nOSError: [Errno 30] Read-only file system: 'answer.json'\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 24, "state": "DONE", "step_type": "agent_response", "duration_seconds": 8.570256519, "usage": {"input_tokens": 2460, "output_tokens": 260, "thinking_tokens": 122, "cache_read_tokens": 46360, "total_tokens": 2720}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 25, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport os, sys\nimport solve\nos.chdir(\"/tmp\")\nsolve.parse_and_solve(\"/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/input.json\", \"/tmp/answer.json\")\nwith open(\"/tmp/answer.json\") as f:\n print(f.read())\n'"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 25, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 1.599964139, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport os, sys\nimport solve\nos.chdir(\"/tmp\")\nsolve.parse_and_solve(\"/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/input.json\", \"/tmp/answer.json\")\nwith open(\"/tmp/answer.json\") as f:\n print(f.read())\n'"}, "output": "Command exited with code 0.\n\nCommand output:\n{\r\n \"counts\": {\r\n \"valid\": 487,\r\n \"bad_checksum\": 11,\r\n \"malformed\": 3\r\n },\r\n \"true_wind_samples\": 95,\r\n \"last\": {\r\n \"tws\": 17.35,\r\n \"twa\": 69.52,\r\n \"twd\": 47.72,\r\n \"vmg\": 1.77,\r\n \"bsp\": 5.06,\r\n \"depth\": 5.6\r\n },\r\n \"tws_mean\": 17.39,\r\n \"tws_max\": 19.79,\r\n \"alarms\": [\r\n {\r\n \"type\": \"speed\",\r\n \"start\": 3,\r\n \"end\": 3\r\n },\r\n {\r\n \"type\": \"speed\",\r\n \"start\": 9,\r\n \"end\": 9\r\n },\r\n {\r\n \"type\": \"speed\",\r\n \"start\": 21,\r\n \"end\": 21\r\n },\r\n {\r\n \"type\": \"speed\",\r\n \"start\": 27,\r\n \"end\": 27\r\n },\r\n {\r\n \"type\": \"speed\",\r\n \"start\": 36,\r\n \"end\": 36\r\n },\r\n {\r\n \"type\": \"speed\",\r\n \"start\": 42,\r\n \"end\": 48\r\n },\r\n {\r\n \"type\": \"speed\",\r\n \"start\": 54,\r\n \"end\": 54\r\n },\r\n {\r\n \"type\": \"speed\",\r\n \"start\": 60,\r\n \"end\": 111\r\n },\r\n {\r\n \"type\": \"wind\",\r\n \"start\": 84,\r\n \"end\": 84\r\n },\r\n {\r\n \"type\": \"wind\",\r\n \"start\": 93,\r\n \"end\": 93\r\n },\r\n {\r\n \"type\": \"wind\",\r\n \"start\": 99,\r\n \"end\": 99\r\n },\r\n {\r\n \"type\": \"speed\",\r\n \"start\": 117,\r\n \"end\": 132\r\n },\r\n {\r\n \"type\": \"speed\",\r\n \"start\": 144,\r\n \"end\": 156\r\n },\r\n {\r\n \"type\": \"speed\",\r\n \"start\": 171,\r\n \"end\": 186\r\n },\r\n {\r\n \"type\": \"speed\",\r\n \"start\": 195,\r\n \"end\": 228\r\n },\r\n {\r\n \"type\": \"depth\",\r\n \"start\": 210,\r\n \"end\": 216\r\n },\r\n {\r\n \"type\": \"speed\",\r\n \"start\": 234,\r\n \"end\": 240\r\n },\r\n {\r\n \"type\": \"speed\",\r\n \"start\": 246,\r\n \"end\": 267\r\n },\r\n {\r\n \"type\": \"speed\",\r\n \"start\": 273,\r\n \"end\": 273\r\n },\r\n {\r\n \"type\": \"speed\",\r\n \"start\": 285,\r\n \"end\": 285\r\n },\r\n {\r\n \"type\": \"speed\",\r\n \"start\": 291,\r\n \"end\": 291\r\n },\r\n {\r\n \"type\": \"depth\",\r\n \"start\": 294,\r\n \"end\": 297\r\n },\r\n {\r\n \"type\": \"speed\",\r\n \"start\": 297,\r\n \"end\": 297\r\n }\r\n ]\r\n}\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 26, "state": "DONE", "step_type": "agent_response", "duration_seconds": 9.710638381999999, "usage": {"input_tokens": 3306, "output_tokens": 485, "thinking_tokens": 61, "cache_read_tokens": 46771, "total_tokens": 3791}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 27, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, re\nfrom html.parser import HTMLParser\n\nwith open(\"/tmp/answer.json\") as f:\n ans = json.load(f)\nwith open(\"/tmp/dashboard.html\") as f:\n html = f.read()\n\nprint(\"dashboard.html length:\", len(html))\nfor forbidden in [\"<script\", \"<img\", \"<link\", \"<iframe\", \"<object\", \"<embed\", \"href=\", \"src=\", \"url(\", \"@import\", \"fetch(\"]:\n assert forbidden not in html.lower(), f\"Forbidden {forbidden} found\"\n\nfor k in [\"tws\", \"twa\", \"twd\", \"vmg\", \"bsp\", \"depth\"]:\n m = re.search(rf\"id=\\\"{k}\\\"\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 27, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 1.9500550909999999, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, re\nfrom html.parser import HTMLParser\n\nwith open(\"/tmp/answer.json\") as f:\n ans = json.load(f)\nwith open(\"/tmp/dashboard.html\") as f:\n html = f.read()\n\nprint(\"dashboard.html length:\", len(html))\nfor forbidden in [\"<script\", \"<img\", \"<link\", \"<iframe\", \"<object\", \"<embed\", \"href=\", \"src=\", \"url(\", \"@import\", \"fetch(\"]:\n assert forbidden not in html.lower(), f\"Forbidden {forbidden} found\"\n\nfor k in [\"tws\", \"twa\", \"twd\", \"vmg\", \"bsp\", \"depth\"]:\n m = re.search(rf\"id=\\\"{k}\\\"\u2026"}, "output": "Command exited with code 1.\n\nCommand output:\n File \"<string>\", line 19\r\n print(f\"{k}: html={val}, ans={ans[\\\"last\\\"][k]}, diff={diff:.4f}\")\r\n ^\r\nSyntaxError: unexpected character after line continuation character\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 28, "state": "DONE", "step_type": "agent_response", "duration_seconds": 8.944647932, "usage": {"input_tokens": 2675, "output_tokens": 464, "thinking_tokens": 46, "cache_read_tokens": 48028, "total_tokens": 3139}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 29, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, re\n\nwith open(\"/tmp/answer.json\") as f:\n ans = json.load(f)\nwith open(\"/tmp/dashboard.html\") as f:\n html = f.read()\n\nfor forbidden in [\"<script\", \"<img\", \"<link\", \"<iframe\", \"<object\", \"<embed\", \"href=\", \"src=\", \"url(\", \"@import\", \"fetch(\"]:\n assert forbidden not in html.lower(), f\"Forbidden {forbidden} found\"\n\nfor k in [\"tws\", \"twa\", \"twd\", \"vmg\", \"bsp\", \"depth\"]:\n m = re.search(f\"id=\\\"{k}\\\"[^>]*>([^<]+)<\", html)\n assert m, f\"Missing {k}\"\n val = float(m.group(1).\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 29, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 2.173400512, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, re\n\nwith open(\"/tmp/answer.json\") as f:\n ans = json.load(f)\nwith open(\"/tmp/dashboard.html\") as f:\n html = f.read()\n\nfor forbidden in [\"<script\", \"<img\", \"<link\", \"<iframe\", \"<object\", \"<embed\", \"href=\", \"src=\", \"url(\", \"@import\", \"fetch(\"]:\n assert forbidden not in html.lower(), f\"Forbidden {forbidden} found\"\n\nfor k in [\"tws\", \"twa\", \"twd\", \"vmg\", \"bsp\", \"depth\"]:\n m = re.search(f\"id=\\\"{k}\\\"[^>]*>([^<]+)<\", html)\n assert m, f\"Missing {k}\"\n val = float(m.group(1).\u2026"}, "output": "Command exited with code 0.\n\nCommand output:\ntws: html=17.4, ans=17.35, diff=0.0500\r\ntwa: html=69.5, ans=69.52, diff=0.0200\r\ntwd: html=47.7, ans=47.72, diff=0.0200\r\nvmg: html=1.8, ans=1.77, diff=0.0300\r\nbsp: html=5.1, ans=5.06, diff=0.0400\r\ndepth: html=5.6, ans=5.6, diff=0.0000\r\nli_count: 23 alarms: 23\r\nALL CHECKS PASSED!\r\n<!DOCTYPE html>\r\n<html lang=\"en\">\r\n<head>\r\n <meta charset=\"utf-8\">\r\n <title>Sailboat Instrument Dashboard</title>\r\n <style>\r\n * { box-sizing: border-box; margin: 0; padding: 0; }\r\n body {\r\n font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Roboto, sans-serif;\r\n background-color: #0b132b;\r\n color: #e0fbfc;\r\n padding: 24px;\r\n }\r\n h1 {\r\n font-size: 22px;\r\n margin-bottom: 20px;\r\n color: #ffffff;\r\n letter-spacing: 0.5px;\r\n }\r\n .layout {\r\n display: grid;\r\n grid-template-columns: 2fr 1fr;\r\n gap: 24px;\r\n max-width: 1080px;\r\n margin: 0 auto;\r\n }\r\n .instruments {\r\n display: grid;\r\n grid-template-columns: repeat(3, 1fr);\r\n gap: 16px;\r\n }\r\n .card {\r\n background-color: #1c2541;\r\n border: 1px solid #3a506b;\r\n border-radius: 10px;\r\n padding: 18px;\r\n text-align: center;\r\n }\r\n .label {\r\n font-size: 13px;\r\n color: #98c1d9;\r\n text-transform: uppercase;\r\n letter-spacing: 1px;\r\n margin-bottom: 8px;\r\n }\r\n .value {\r\n font-size: 36px;\r\n font-weight: 700;\r\n color: #ffffff;\r\n }\r\n .unit {\r\n font-size: 13px;\r\n color: #5bc0be;\r\n margin-top: 4px;\r\n }\r\n .panel {\r\n background-color: #1c2541;\r\n border: 1px solid #3a506b;\r\n border-radius: 10px;\r\n padding: 18px;\r\n display: flex;\r\n flex-direction: column;\r\n align-items: center;\r\n }\r\n .alarms-panel {\r\n margin-top: 24px;\r\n max-width: 1080px;\r\n margin-left: auto;\r\n margin-right: auto;\r\n background-color: #1c2541;\r\n border: 1px solid #3a506b;\r\n border-radius: 10px;\r\n padding: 18px;\r\n }\r\n .alarms-title {\r\n font-size: 15px;\r\n color: #98c1d9;\r\n text-transform: uppercase;\r\n letter-spacing: 1px;\r\n margin-bottom: 12px;\r\n }\r\n #alarm-list {\r\n list-style: none;\r\n display: grid;\r\n grid-template-columns: repeat(auto-fill, minmax(200px, 1fr));\r\n gap: 8px;\r\n }\r\n .alarm-item {\r\n background-color: #0b132b;\r\n border: 1px solid #3a506b;\r\n border-radius: 6px;\r\n padding: 8px 12px;\r\n font-size: 13px;\r\n display: flex;\r\n justify-content: space-between;\r\n align-items: center;\r\n }\r\n .badge {\r\n font-weight: 700;\r\n font-size: 11px;\r\n padding: 2px 6px;\r\n border-radius: 4px;\r\n }\r\n .alarm-depth .badge { background-color: #e63946; color: #ffffff; }\r\n .alarm-wind .badge { background-color: #f4a261; color: #0b132b; }\r\n .alarm-speed .badge { background-color: #2a9d8f; color: #ffffff; }\r\n </style>\r\n</head>\r\n<body>\r\n <div class=\"layout\">\r\n <div>\r\n <h1>Sailboat Instrument Telemetry</h1>\r\n <div class=\"instruments\">\r\n <div class=\"card\">\r\n <div class=\"label\">True Wind Speed</div>\r\n <div class=\"value\" id=\"tws\">17.4</div>\r\n <div class=\"unit\">knots</div>\r\n </div>\r\n <div class=\"card\">\r\n <div class=\"label\">True Wind Angle</div>\r\n <div class=\"value\" id=\"twa\">69.5</div>\r\n <div class=\"unit\">deg</div>\r\n </div>\r\n <div class=\"card\">\r\n <div class=\"label\">True Wind Dir</div>\r\n <div class=\"value\" id=\"twd\">47.7</div>\r\n <div class=\"unit\">deg</div>\r\n </div>\r\n <div class=\"card\">\r\n <div class=\"label\">Velocity Made Good</div>\r\n <div class=\"value\" id=\"vmg\">1.8</div>\r\n <div class=\"unit\">knots</div>\r\n </div>\r\n <div class=\"card\">\r\n <div class=\"label\">Boat Speed</div>\r\n <div class=\"value\" id=\"bsp\">5.1</div>\r\n <div class=\"unit\">knots</div>\r\n </div>\r\n <div class=\"card\">\r\n <div class=\"label\">Water Depth</div>\r\n <div class=\"value\" id=\"depth\">5.6</div>\r\n <div class=\"unit\">metres</div>\r\n </div>\r\n </div>\r\n </div>\r\n <div class=\"panel\">\r\n <div class=\"label\">Wind Rose (TWD)</div>\r\n <svg id=\"wind-rose\" width=\"240\" height=\"240\" viewBox=\"0 0 240 240\">\r\n <circle cx=\"120\" cy=\"120\" r=\"95\" fill=\"#0b132b\" stroke=\"#3a506b\" stroke-width=\"2\" />\r\n <circle cx=\"120\" cy=\"120\" r=\"65\" fill=\"none\" stroke=\"#1c2541\" stroke-width=\"1\" stroke-dasharray=\"4 4\" />\r\n <text x=\"120\" y=\"20\" text-anchor=\"middle\" fill=\"#98c1d9\" font-size=\"12\" font-weight=\"bold\">N</text>\r\n <text x=\"224\" y=\"124\" text-anchor=\"middle\" fill=\"#98c1d9\" font-size=\"12\" font-weight=\"bold\">E</text>\r\n <text x=\"120\" y=\"232\" text-anchor=\"middle\" fill=\"#98c1d9\" font-size=\"12\" font-weight=\"bold\">S</text>\r\n <text x=\"16\" y=\"124\" text-anchor=\"middle\" fill=\"#98c1d9\" font-size=\"12\" font-weight=\"bold\">W</text>\r\n <line id=\"twd-needle\" x1=\"120.0\" y1=\"120.0\" x2=\"185.11\" y2=\"60.80\" stroke=\"#5bc0be\" stroke-width=\"4\" stroke-linecap=\"round\" />\r\n <circle cx=\"120\" cy=\"120\" r=\"5\" fill=\"#ffffff\" />\r\n </svg>\r\n </div>\r\n </div>\r\n <div class=\"alarms-panel\">\r\n <div class=\"alarms-title\">Alarms (23)</div>\r\n <ul id=\"alarm-list\">\r\n <li class=\"alarm-item alarm-speed\"><span class=\"badge\">SPEED</span> <span>3s – 3s</span></li>\r\n <li class=\"alarm-item alarm-speed\"><span class=\"badge\">SPEED</span> <span>9s – 9s</span></li>\r\n <li class=\"alarm-item alarm-speed\"><span class=\"badge\">SPEED</span> <span>21s – 21s</span></li>\r\n <li class=\"alarm-item alarm-speed\"><span class=\"badge\">SPEED</span> <span>27s – 27s</span></li>\r\n <li class=\"alarm-item alarm-speed\"><span class=\"badge\">SPEED</span> <span>36s – 36s</span></li>\r\n <li class=\"alarm-item alarm-speed\"><span class=\"badge\">SPEED</span> <span>42s – 48s</span></li>\r\n <li class=\"alarm-item alarm-speed\"><span class=\"badge\">SPEED</span> <span>54s – 54s</span></li>\r\n <li class=\"alarm-item alarm-speed\"><span class=\"badge\">SPEED</span> <span>60s – 111s</span></li>\r\n <li class=\"alarm-item alarm-wind\"><span class=\"badge\">WIND</span> <span>84s – 84s</span></li>\r\n <li class=\"alarm-item alarm-wind\"><span class=\"badge\">WIND</span> <span>93s – 93s</span></li>\r\n <li class=\"alarm-item alarm-wind\"><span class=\"badge\">WIND</span> <span>99s – 99s</span></li>\r\n <li class=\"alarm-item alarm-speed\"><span class=\"badge\">SPEED</span> <span>117s – 132s</span></li>\r\n <li class=\"alarm-item alarm-speed\"><span class=\"badge\">SPEED</span> <span>144s – 156s</span></li>\r\n <li class=\"alarm-item alarm-speed\"><span class=\"badge\">SPEED</span> <span>171s – 186s</span></li>\r\n <li class=\"alarm-item alarm-speed\"><span class=\"badge\">SPEED</span> <span>195s – 228s</span></li>\r\n <li class=\"alarm-item alarm-depth\"><span class=\"badge\">DEPTH</span> <span>210s – 216s</span></li>\r\n <li class=\"alarm-item alarm-speed\"><span class=\"badge\">SPEED</span> <span>234s – 240s</span></li>\r\n <li class=\"alarm-item alarm-speed\"><span class=\"badge\">SPEED</span> <span>246s – 267s</span></li>\r\n <li class=\"alarm-item alarm-speed\"><span class=\"badge\">SPEED</span> <span>273s – 273s</span></li>\r\n <li class=\"alarm-item alarm-speed\"><span class=\"badge\">SPEED</span> <span>285s – 285s</span></li>\r\n <li class=\"alarm-item alarm-speed\"><span class=\"badge\">SPEED</span> <span>291s – 291s</span></li>\r\n <li class=\"alarm-item alarm-depth\"><span class=\"badge\">DEPTH</span> <span>294s – 297s</span></li>\r\n <li class=\"alarm-item alarm-speed\"><span class=\"badge\">SPEED</span> <span>297s – 297s</span></li>\r\n </ul>\r\n </div>\r\n</body>\r\n</html>\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 30, "state": "DONE", "step_type": "agent_response", "duration_seconds": 11.554038513, "usage": {"input_tokens": 3380, "output_tokens": 663, "thinking_tokens": 453, "cache_read_tokens": 50704, "total_tokens": 4043}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 31, "state": "ACTIVE", "step_type": "tool", "tool_name": "edit_file", "tool_info": {"name": "edit_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/solve.py"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 31, "state": "DONE", "step_type": "tool", "tool_name": "edit_file", "duration_seconds": 1.595573526, "tool_info": {"name": "edit_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/solve.py"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 32, "state": "DONE", "step_type": "agent_response", "duration_seconds": 52.734555964, "usage": {"input_tokens": 2841, "output_tokens": 3783, "thinking_tokens": 97, "cache_read_tokens": 52035, "total_tokens": 6624}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 33, "state": "ACTIVE", "step_type": "tool", "tool_name": "write_file", "tool_info": {"name": "write_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/answer.json"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 33, "state": "DONE", "step_type": "tool", "tool_name": "write_file", "duration_seconds": 1.715475858, "tool_info": {"name": "write_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/answer.json"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 34, "state": "ACTIVE", "step_type": "tool", "tool_name": "write_file", "tool_info": {"name": "write_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/dashboard.html"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 34, "state": "DONE", "step_type": "tool", "tool_name": "write_file", "duration_seconds": 3.1831833019999998, "tool_info": {"name": "write_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/dashboard.html"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "I"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " have implemented [solve"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": ".py](file://"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "/home/bob/usecase-runs/a"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "gy-batch/out"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "/"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "gemini-4-argon-medium/k01/work/solve"}}
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{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "shboard.html"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "](file:///home/bob/"}}
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{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "argon-medium/k01/work"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "/dashboard.html):\n\n- **["}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "`parse_and_s"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "olve`](file:///home/bob/"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "usecase-runs/agy-batch"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "/out/gemini-4-argon-medium/k01/work/"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "solve.py#L7-"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "L388)**:\n - Parses `<t>"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": ",<sentence>`"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " lines, ignoring blank l"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ines, valida"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ting XOR checksums ("}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "`bad_checksum`), and classifying str"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "uctural or required-fiel"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "d errors (`malformed`).\n"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " - Tracks l"}}
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{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "oat speed (`"}}
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{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "`), depth (`DBT`), and speed over gr"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ound (`VTG`), computing "}}
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{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "s on `MWV` sentences wit"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "h reference `R` and stat"}}
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{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "\n - Finds consecutive b"}}
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{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "th`, `wind`,"}}
{"event": "step_update", "step_update": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "step_index": 35, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " `speed`) sorted by `(st"}}
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{"event": "result", "result": {"conversation_id": "b9d9ed9b-42c6-4ee1-8118-6fa358fdc7bc", "status": "SUCCESS", "response": "I have implemented [solve.py](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/solve.py) and generated [answer.json](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/answer.json) and [dashboard.html](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/dashboard.html):\n\n- **[`parse_and_solve`](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/solve.py#L7-L388)**:\n - Parses `<t>,<sentence>` lines, ignoring blank lines, validating XOR checksums (`bad_checksum`), and classifying structural or required-field errors (`malformed`).\n - Tracks latest heading (`HDT`), boat speed (`VHW`), depth (`DBT`), and speed over ground (`VTG`), computing true wind (`TWS`, `TWA`, `TWD`) and `VMG` samples on `MWV` sentences with reference `R` and status `A`.\n - Finds consecutive breaking runs per sensor stream (`depth`, `wind`, `speed`) sorted by `(start, type)`.\n - Writes [answer.json](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/answer.json) and self-contained static [dashboard.html](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k01/work/dashboard.html) containing `#tws`, `#twa`, `#twd`, `#vmg`, `#bsp`, `#depth`, `<svg id=\"wind-rose\">` with `<line id=\"twd-needle\">`, and `<ul id=\"alarm-list\">`.\n", "duration_seconds": 488.418842424, "num_turns": 1, "usage": {"input_tokens": 71103, "output_tokens": 24707, "thinking_tokens": 11828, "cache_read_tokens": 602954, "total_tokens": 95810}}}